Matlab Code for Permuted Parallel Compressed Sensing of 2D Sparse Signals

(August 2013)
Hao Fan, Sergiy A. Vorobyov, Hai Jiang, and Omid Taheri

License and Referencing

This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article H. Fan, S.A. Vorobyov, H. Jiang, and O. Taheri, "Permutation meets parallel compressed sensing: How to relax restricted isometry property for 2D sparse signals," IEEE Trans. Signal Processing, vol. 62, no. 1, pp. 196210, Jan. 2014.

Purpose

This is a code package is related to the following scientific article:

 

H. Fan, S.A. Vorobyov, H. Jiang, and O. Taheri, "Permutation meets parallel compressed sensing: How to relax restricted isometry property for 2D sparse signals," IEEE Trans. Signal Processing, vol. 62, no. 1, pp. 196210, Jan. 2014.

 

The package contains a simulation environment, based on Matlab, that reproduces all the numerical results and figures in the article. We encourage you to also perform reproducible research!

Feedback

Please report any bugs to Sergiy A. Vorobyov <svor@ieee.org>.

Download

CSimage.zip